Geospatial Data Mining
Objectives
Geospatial Data Mining (GSDM) has distinct characteristics from general data mining (DM) conducted based on company data. Although a large number of coincidences exist between them, there are some differences, which are very important and must not be neglected. This course aims to present the methodology of data mining, as well as its main tools and further emphasize the specifics that exist in geospatial data exploration. Thus, by the end of this course, students should have a good understanding of the main tools of data mining, as well as critical thinking regarding its application in the context of geographic information science (GISc)
General characterization
Code
200060
Credits
7.5
Responsible teacher
Roberto André Pereira Henriques
Hours
Weekly - Available soon
Total - Available soon
Teaching language
Portuguese. If there are Erasmus students, classes will be taught in English
Prerequisites
None
Bibliography
Papers will be supplied for each module of the course; 0; 0; 0; 0
Teaching method
The unit (UC) is based on problem oriented approach with the active acquisition of knowledge by students.
The UC consists of asynchronous reading of various materials and on the realization of projects and a synchronous part that consists of classroom sessions and tutorials.
Evaluation method
A final exam (30%) Four individual projects: two theoretical (10% each) and 2 practical (25% and 20%)
Subject matter
1. Introduction to Geospatial Data Mining
2. The role of data mining in the GIsc
3. Unsupervised Classification
4. Supervised Classification
Programs
Programs where the course is taught:
- e-learning - Specialization in Geographic Information Systems and Science
- e-learning - Specialization in Geospatial Data Science
- Master in Science of Geospatial Technologies
- Master in Geographic Information Systems and Science
- PostGraduate in Smart Cities
- Post-Graduation in Geographic Information Systems and Science
- b-learning - Specialization in Geospatial Data Science